Garbage collection is a widely used technique that frees the programmer from
having to know the lifetimes of heap objects, making software easier to produce
and maintain. Many programming languages rely on garbage collection for
automatic memory management. There are two primary forms of garbage collection:
conservative and accurate.

Conservative garbage collection often does not require any special support
from either the language or the compiler: it can handle non-type-safe
programming languages (such as C/C++) and does not require any special
information from the compiler. The
Boehm collector is
an example of a state-of-the-art conservative collector.

Accurate garbage collection requires the ability to identify all pointers in
the program at run-time (which requires that the source-language be type-safe in
most cases). Identifying pointers at run-time requires compiler support to
locate all places that hold live pointer variables at run-time, including the
processor stack and registers.

Conservative garbage collection is attractive because it does not require any
special compiler support, but it does have problems. In particular, because the
conservative garbage collector cannot know that a particular word in the
machine is a pointer, it cannot move live objects in the heap (preventing the
use of compacting and generational GC algorithms) and it can occasionally suffer
from memory leaks due to integer values that happen to point to objects in the
program. In addition, some aggressive compiler transformations can break
conservative garbage collectors (though these seem rare in practice).

Accurate garbage collectors do not suffer from any of these problems, but
they can suffer from degraded scalar optimization of the program. In particular,
because the runtime must be able to identify and update all pointers active in
the program, some optimizations are less effective. In practice, however, the
locality and performance benefits of using aggressive garbage collection
techniques dominates any low-level losses.

This document describes the mechanisms and interfaces provided by LLVM to
support accurate garbage collection.

LLVM's intermediate representation provides garbage
collection intrinsics that offer support for a broad class of
collector models. For instance, the intrinsics permit:

semi-space collectors

mark-sweep collectors

generational collectors

reference counting

incremental collectors

concurrent collectors

cooperative collectors

We hope that the primitive support built into the LLVM IR is sufficient to
support a broad class of garbage collected languages including Scheme, ML, Java,
C#, Perl, Python, Lua, Ruby, other scripting languages, and more.

However, LLVM does not itself provide a garbage collectorthis should
be part of your language's runtime library. LLVM provides a framework for
compile time code generation plugins. The role of these
plugins is to generate code and data structures which conforms to the binary
interface specified by the runtime library. This is similar to the
relationship between LLVM and DWARF debugging info, for example. The
difference primarily lies in the lack of an established standard in the domain
of garbage collectionthus the plugins.

The aspects of the binary interface with which LLVM's GC support is
concerned are:

Creation of GC-safe points within code where collection is allowed to
execute safely.

Computation of the stack map. For each safe point in the code, object
references within the stack frame must be identified so that the
collector may traverse and perhaps update them.

Write barriers when storing object references to the heap. These are
commonly used to optimize incremental scans in generational
collectors.

Emission of read barriers when loading object references. These are
useful for interoperating with concurrent collectors.

There are additional areas that LLVM does not directly address:

Registration of global roots with the runtime.

Registration of stack map entries with the runtime.

The functions used by the program to allocate memory, trigger a
collection, etc.

Computation or compilation of type maps, or registration of them with
the runtime. These are used to crawl the heap for object
references.

In general, LLVM's support for GC does not include features which can be
adequately addressed with other features of the IR and does not specify a
particular binary interface. On the plus side, this means that you should be
able to integrate LLVM with an existing runtime. On the other hand, it leaves
a lot of work for the developer of a novel language. However, it's easy to get
started quickly and scale up to a more sophisticated implementation as your
compiler matures.

Use @llvm.gcread and/or @llvm.gcwrite to
manipulate GC references, if necessary.

Allocate memory using the GC allocation routine provided by the
runtime library.

Generate type maps according to your runtime's binary interface.

Write a compiler plugin to interface LLVM with the runtime library.*

Lower @llvm.gcread and @llvm.gcwrite to appropriate
code sequences.*

Compile LLVM's stack map to the binary form expected by the
runtime.

Load the plugin into the compiler. Use llc -load or link the
plugin statically with your language's compiler.*

Link program executables with the runtime.

To help with several of these tasks (those indicated with a *), LLVM
includes a highly portable, built-in ShadowStack code generator. It is compiled
into llc and works even with the interpreter and C backends.

for each function your compiler emits. Since the shadow stack is built into
LLVM, you do not need to load a plugin.

Your compiler must also use @llvm.gcroot as documented.
Don't forget to create a root for each intermediate value that is generated
when evaluating an expression. In h(f(), g()), the result of
f() could easily be collected if evaluating g() triggers a
collection.

There's no need to use @llvm.gcread and @llvm.gcwrite over
plain load and store for now. You will need them when
switching to a more advanced GC.

The shadow stack doesn't imply a memory allocation algorithm. A semispace
collector or building atop malloc are great places to start, and can
be implemented with very little code.

When it comes time to collect, however, your runtime needs to traverse the
stack roots, and for this it needs to integrate with the shadow stack. Luckily,
doing so is very simple. (This code is heavily commented to help you
understand the data structure, but there are only 20 lines of meaningful
code.)

/// @brief The map for a single function's stack frame. One of these is
/// compiled as constant data into the executable for each function.
///
/// Storage of metadata values is elided if the %metadata parameter to
/// @llvm.gcroot is null.
struct FrameMap {
int32_t NumRoots; //< Number of roots in stack frame.
int32_t NumMeta; //< Number of metadata entries. May be < NumRoots.
const void *Meta[0]; //< Metadata for each root.
};
/// @brief A link in the dynamic shadow stack. One of these is embedded in the
/// stack frame of each function on the call stack.
struct StackEntry {
StackEntry *Next; //< Link to next stack entry (the caller's).
const FrameMap *Map; //< Pointer to constant FrameMap.
void *Roots[0]; //< Stack roots (in-place array).
};
/// @brief The head of the singly-linked list of StackEntries. Functions push
/// and pop onto this in their prologue and epilogue.
///
/// Since there is only a global list, this technique is not threadsafe.
StackEntry *llvm_gc_root_chain;
/// @brief Calls Visitor(root, meta) for each GC root on the stack.
/// root and meta are exactly the values passed to
/// @llvm.gcroot.
///
/// Visitor could be a function to recursively mark live objects. Or it
/// might copy them to another heap or generation.
///
/// @param Visitor A function to invoke for every GC root on the stack.
void visitGCRoots(void (*Visitor)(void **Root, const void *Meta)) {
for (StackEntry *R = llvm_gc_root_chain; R; R = R->Next) {
unsigned i = 0;
// For roots [0, NumMeta), the metadata pointer is in the FrameMap.
for (unsigned e = R->Map->NumMeta; i != e; ++i)
Visitor(&R->Roots[i], R->Map->Meta[i]);
// For roots [NumMeta, NumRoots), the metadata pointer is null.
for (unsigned e = R->Map->NumRoots; i != e; ++i)
Visitor(&R->Roots[i], NULL);
}
}

Unlike many GC algorithms which rely on a cooperative code generator to
compile stack maps, this algorithm carefully maintains a linked list of stack
roots [Henderson2002]. This so-called "shadow stack"
mirrors the machine stack. Maintaining this data structure is slower than using
a stack map compiled into the executable as constant data, but has a significant
portability advantage because it requires no special support from the target
code generator, and does not require tricky platform-specific code to crawl
the machine stack.

The tradeoff for this simplicity and portability is:

High overhead per function call.

Not thread-safe.

Still, it's an easy way to get started. After your compiler and runtime are
up and running, writing a plugin will allow you to take
advantage of more advanced GC features of LLVM
in order to improve performance.

These facilities are limited to those strictly necessary; they are not
intended to be a complete interface to any garbage collector. A program will
need to interface with the GC library using the facilities provided by that
program.

The gc function attribute is used to specify the desired GC style
to the compiler. Its programmatic equivalent is the setGC method of
Function.

Setting gc "name" on a function triggers a search for a
matching code generation plugin "name"; it is that plugin which defines
the exact nature of the code generated to support GC. If none is found, the
compiler will raise an error.

Specifying the GC style on a per-function basis allows LLVM to link together
programs that use different garbage collection algorithms (or none at all).

The llvm.gcroot intrinsic is used to inform LLVM that a stack
variable references an object on the heap and is to be tracked for garbage
collection. The exact impact on generated code is specified by a compiler plugin.

A compiler which uses mem2reg to raise imperative code using alloca
into SSA form need only add a call to @llvm.gcroot for those variables
which a pointers into the GC heap.

It is also important to mark intermediate values with llvm.gcroot.
For example, consider h(f(), g()). Beware leaking the result of
f() in the case that g() triggers a collection.

The first argument must be a value referring to an alloca instruction
or a bitcast of an alloca. The second contains a pointer to metadata that
should be associated with the pointer, and must be a constant or global
value address. If your target collector uses tags, use a null pointer for
metadata.

The %metadata argument can be used to avoid requiring heap objects
to have 'isa' pointers or tag bits. [Appel89, Goldberg91, Tolmach94] If
specified, its value will be tracked along with the location of the pointer in
the stack frame.

Consider the following fragment of Java code:

{
Object X; // A null-initialized reference to an object
...
}

This block (which may be located in the middle of a function or in a loop
nest), could be compiled to this LLVM code:

Entry:
;; In the entry block for the function, allocate the
;; stack space for X, which is an LLVM pointer.
%X = alloca %Object*
;; Tell LLVM that the stack space is a stack root.
;; Java has type-tags on objects, so we pass null as metadata.
%tmp = bitcast %Object** %X to i8**
call void @llvm.gcroot(i8** %X, i8* null)
...
;; "CodeBlock" is the block corresponding to the start
;; of the scope above.
CodeBlock:
;; Java null-initializes pointers.
store %Object* null, %Object** %X
...
;; As the pointer goes out of scope, store a null value into
;; it, to indicate that the value is no longer live.
store %Object* null, %Object** %X
...

Some collectors need to be informed when the mutator (the program that needs
garbage collection) either reads a pointer from or writes a pointer to a field
of a heap object. The code fragments inserted at these points are called
read barriers and write barriers, respectively. The amount of
code that needs to be executed is usually quite small and not on the critical
path of any computation, so the overall performance impact of the barrier is
tolerable.

Barriers often require access to the object pointer rather than the
derived pointer (which is a pointer to the field within the
object). Accordingly, these intrinsics take both pointers as separate arguments
for completeness. In this snippet, %object is the object pointer, and
%derived is the derived pointer:

LLVM does not enforce this relationship between the object and derived
pointer (although a plugin might). However, it would be
an unusual collector that violated it.

The use of these intrinsics is naturally optional if the target GC does
require the corresponding barrier. Such a GC plugin will replace the intrinsic
calls with the corresponding load or store instruction if they
are used.

For write barriers, LLVM provides the llvm.gcwrite intrinsic
function. It has exactly the same semantics as a non-volatile store to
the derived pointer (the third argument). The exact code generated is specified
by a compiler plugin.

Many important algorithms require write barriers, including generational
and concurrent collectors. Additionally, write barriers could be used to
implement reference counting.

For read barriers, LLVM provides the llvm.gcread intrinsic function.
It has exactly the same semantics as a non-volatile load from the
derived pointer (the second argument). The exact code generated is specified by
a compiler plugin.

Read barriers are needed by fewer algorithms than write barriers, and may
have a greater performance impact since pointer reads are more frequent than
writes.

User code specifies which GC code generation to use with the gc
function attribute or, equivalently, with the setGC method of
Function.

To implement a GC plugin, it is necessary to subclass
llvm::GCStrategy, which can be accomplished in a few lines of
boilerplate code. LLVM's infrastructure provides access to several important
algorithms. For an uncontroversial collector, all that remains may be to
compile LLVM's computed stack map to assembly code (using the binary
representation expected by the runtime library). This can be accomplished in
about 100 lines of code.

This is not the appropriate place to implement a garbage collected heap or a
garbage collector itself. That code should exist in the language's runtime
library. The compiler plugin is responsible for generating code which
conforms to the binary interface defined by library, most essentially the
stack map.

GCStrategy provides a range of features through which a plugin
may do useful work. Some of these are callbacks, some are algorithms that can
be enabled, disabled, or customized. This matrix summarizes the supported (and
planned) features and correlates them with the collection techniques which
typically require them.

The mutator maintains a reference count for each object and frees an
object when its count falls to zero.

Mark-Sweep

When the heap is exhausted, the collector marks reachable objects starting
from the roots, then deallocates unreachable objects in a sweep
phase.

Copying

As reachability analysis proceeds, the collector copies objects from one
heap area to another, compacting them in the process. Copying collectors
enable highly efficient "bump pointer" allocation and can improve locality
of reference.

Incremental

(Including generational collectors.) Incremental collectors generally have
all the properties of a copying collector (regardless of whether the
mature heap is compacting), but bring the added complexity of requiring
write barriers.

Threaded

Denotes a multithreaded mutator; the collector must still stop the mutator
("stop the world") before beginning reachability analysis. Stopping a
multithreaded mutator is a complicated problem. It generally requires
highly platform specific code in the runtime, and the production of
carefully designed machine code at safe points.

Concurrent

In this technique, the mutator and the collector run concurrently, with
the goal of eliminating pause times. In a cooperative collector,
the mutator further aids with collection should a pause occur, allowing
collection to take advantage of multiprocessor hosts. The "stop the world"
problem of threaded collectors is generally still present to a limited
extent. Sophisticated marking algorithms are necessary. Read barriers may
be necessary.

As the matrix indicates, LLVM's garbage collection infrastructure is already
suitable for a wide variety of collectors, but does not currently extend to
multithreaded programs. This will be added in the future as there is
interest.

LLVM automatically computes a stack map. One of the most important features
of a GCStrategy is to compile this information into the executable in
the binary representation expected by the runtime library.

The stack map consists of the location and identity of each GC root in the
each function in the module. For each root:

RootNum: The index of the root.

StackOffset: The offset of the object relative to the frame
pointer.

RootMetadata: The value passed as the %metadata
parameter to the @llvm.gcroot intrinsic.

Also, for the function as a whole:

getFrameSize(): The overall size of the function's initial
stack frame, not accounting for any dynamic allocation.

roots_size(): The count of roots in the function.

To access the stack map, use GCFunctionMetadata::roots_begin() and
-end() from the GCMetadataPrinter:

If the llvm.gcroot intrinsic is eliminated before code generation by
a custom lowering pass, LLVM will compute an empty stack map. This may be useful
for collector plugins which implement reference counting or a shadow stack.

When set, LLVM will automatically initialize each root to null upon
entry to the function. This prevents the GC's sweep phase from visiting
uninitialized pointers, which will almost certainly cause it to crash. This
initialization occurs before custom lowering, so the two may be used
together.

Since LLVM does not yet compute liveness information, there is no means of
distinguishing an uninitialized stack root from an initialized one. Therefore,
this feature should be used by all GC plugins. It is enabled by default.

Almost every collector requires PostCall safe points, since these
correspond to the moments when the function is suspended during a call to a
subroutine.

Threaded programs generally require Loop safe points to guarantee
that the application will reach a safe point within a bounded amount of time,
even if it is executing a long-running loop which contains no function
calls.

Threaded collectors may also require Return and PreCall
safe points to implement "stop the world" techniques using self-modifying code,
where it is important that the program not exit the function without reaching a
safe point (because only the topmost function has been patched).

LLVM allows a plugin to print arbitrary assembly code before and after the
rest of a module's assembly code. At the end of the module, the GC can compile
the LLVM stack map into assembly code. (At the beginning, this information is not
yet computed.)

Since AsmWriter and CodeGen are separate components of LLVM, a separate
abstract base class and registry is provided for printing assembly code, the
GCMetadaPrinter and GCMetadataPrinterRegistry. The AsmWriter
will look for such a subclass if the GCStrategy sets
UsesMetadata:

MyGC::MyGC() {
UsesMetadata = true;
}

This separation allows JIT-only clients to be smaller.

Note that LLVM does not currently have analogous APIs to support code
generation in the JIT, nor using the object writers.

The collector should use AsmPrinter and TargetAsmInfo to
print portable assembly code to the std::ostream. The collector itself
contains the stack map for the entire module, and may access the
GCFunctionInfo using its own begin() and end()
methods. Here's a realistic example: